Cookies, Spreadsheets, and
Modeling: Dynamic, Interactive,
Visual Science and Math
A Preview of the PSC CAST Professional Development Modules using Excel
Scott A. Sinex
Prince George’s Community College
Presented at Network Connections, Pittsburgh, PA on 27 October 2011
The agenda for today
• The Pittsburgh Supercomputing Center’s
CAST Professional Development Modules
• Building a mathematical model with
cookies
• Using spreadsheet simulations to enhance
a model
• A taste of constructing a simulation in
Excel
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Computation and Science for
Teachers (CAST)
• A program to infuse computational reasoning
into secondary math and science instruction
• A collaboration of the Pittsburgh
Supercomputing Center (PSC), the Maryland
Virtual High School (MVHS) and the
Southwest PA Math & Science Collaborative
(MSC)
• A Professional Development Experience for
middle and high school math and science
teachers.
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The Pittsburgh Supercomputing Center
• A University-based computing and
research organization serving scientists
and researchers across the nation.
• Mission: Provide state of the art high
performance computing environments for
solving large-scale computational problems
in all fields of science such as:
– Violent storm modeling
– Molecular biology
– Origins of the universe
PSC offices are located at 300 S.
Craig St., on the campus of Carnegie
Mellon University in Pittsburgh,
Pennsylvania.
• New educational mission: introduce tools of
computational scientists to secondary
school math and science teachers
4
CAST Goals
The goals of the CAST program are to:
• Increase the use of computational reasoning to
support theory and experimentation in scientific
inquiry.
• Increase the use of interactive computational
tools such as modeling and simulation to
support the teaching of scientific and
mathematical concepts.
• Improve the learning experience and
engagement of students in math and science.
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What is Computational Reasoning?
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
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Understanding how to analyze, visualize and
represent data using mathematical and
computational tools
Using computer models to support theory and
experimentation in scientific inquiry
Using models and simulations as interactive
tools for understanding complex concepts in
science and mathematics
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Why Computational Reasoning?
Addresses Common Core Standards in Mathematics
 Standards for Mathematical Practices
•
•
•
•
MODEL WITH MATHEMATICS
Reason abstractly and quantitatively
Use appropriate tools strategically
Look for and express regularity in repeated reasoning
 Standards for Mathematical Content
• Making Inferences and Justifying Conclusions
o
Understand and evaluate random processes underlying statistical
experiments
o
Make inferences and justify conclusions from sample surveys,
experiments and observational studies.
http://www.corestandards.org/assets/CCSSI_Math%20Standards.pdf
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Why Computational Reasoning?
Supports Science Practices recommended by the
2011 Framework for K-12 Science Education

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Developing and using models
Using mathematics, information and computer technology, and
computational thinking
Supports teaching science as inquiry by providing:

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Models of real world events that are difficult to demonstrate in wet lab
experiments
Opportunities for careful observation and analysis of scientific
investigations
The ability to test hypotheses, analyze results, form explanations,
judge the logic and consistency of conclusions, and predict future
outcomes.
http://www7.nationalacademies.org/bose/Standards_Framework_Homepage.html
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CAST Two-Track Program
Track one – seven modules on how to USE
models (already available over the web) in the
classroom
Track two – five modules on how to CREATE or
customize your own models for the classroom
Both tracks explore three modeling tools:
- Excel models - Today a taste of this tool!
- Agent models
- System or Aggregate models
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The big picture…
Multiple representations
A multivariable
approach
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Goals for today
 Develop a mathematical model from
experimental data
 Make predictions with the model
 Consider variations in the model and their
influence
 Graphical interpretation – What is the graph
telling me?
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Our hypothesis…
• Is there a relationship between the height
of a stack of Oreo cookies and the number
of cookies in the stack?
• If so, how could we find this relationship?
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Collect the data
• Stack cookies
• Measure to nearest 0.1cm
• Open cookie_stack.xls
• Enter into “just add data” Excelet
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“Just add data” Excelet
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What does the mathematical model
or equation mean?
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What about errors in the model?
• Where can errors originate?
– Measurement
– Manufacturing
16
More about errors
• What should the y-intercept be for the
mathematical model?
• Why doesn’t the mathematical model have
a y-intercept of zero?
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Scatter in the data
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If we repeated the experiment but
mixed regular Oreos with DoubleStuf Oreos, how would our results
turn out?
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Building a simulation
• Let’s construct a model for the behavior of
the quadratic equation
• Our multivariable equation
y = ax2 + bx + c
• How does the graph behave when we vary
a, b, and c?
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Set-up screen
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Simulation of quadratic equation
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What did you learn today?
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Want to learn even more?
• PSC CAST PD modules
http://www.psc.edu/eot/cast
• Developer’s Guide to Excelets
http://academic.pgcc.edu/~ssinex/excelets
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For more info…
• For PSC CAST Professional Development
Modules: Cheryl Begandy
begandy@psc.edu
• For Excelets: Scott Sinex
ssinex@pgcc.edu
THANKS FOR ATTENDING TODAY